CN113409229A - Method for evaluating contour of abrasive particles of large-abrasive-particle superhard abrasive grinding wheel - Google Patents
Method for evaluating contour of abrasive particles of large-abrasive-particle superhard abrasive grinding wheel Download PDFInfo
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Abstract
The invention discloses a method for evaluating the contour of large-abrasive-grain superhard abrasive grinding wheel abrasive grains, and belongs to the technical field of grinding wheel finishing and image recognition processing. The method of the invention comprises the following steps: firstly, detecting three-dimensional data on the surface of a large-abrasive-particle superhard abrasive grinding wheel by using an ultra-high-speed profile measuring instrument, and adjusting a mounting fixture to ensure that the circular runout of the grinding wheel is within 10 mu m before detection (measuring by using a dial indicator); and then, carrying out binarization image processing such as singular point and noise point removal, connected domain analysis, image corrosion and the like by Matlab software to obtain the quantity of the abrasive particles of the reference surface at a specific height at intervals. And finally, carrying out rule analysis and research on the abrasive particle exposure height information. The invention combines the laser detection technology, the data processing technology and the image processing technology, and realizes the accurate evaluation of the high performance of the large-abrasive-grain super-abrasive grinding wheel abrasive grains.
Description
Technical Field
The invention relates to a shaping technology and an image acquisition, processing and analysis method for a large-abrasive-particle superhard abrasive grinding wheel, belongs to the technical field of grinding wheel finishing technology and image recognition processing, and particularly relates to a high-performance evaluation method for large-abrasive-particle superhard abrasive grinding wheel abrasive particles.
Background
The large-abrasive-grain superhard abrasive grinding wheel has the advantages of reducing the complexity and randomness of the grinding process, improving the dynamic sharpness of the grinding wheel and the like, optimizes and matches the process parameters in the grinding process to the maximum extent, achieves the purpose of actively controlling the motion track of abrasive grains, and is widely applied to the grinding field. However, since it is difficult to ensure consistent exposure heights of abrasive grains after the large-abrasive-grain superabrasive grinding wheel is manufactured, the actual cutting depth of each abrasive grain is greatly different, and the surface quality of a ground workpiece is affected. Therefore, it is necessary to efficiently shape a large-abrasive-grain superabrasive grinding wheel and evaluate the surface abrasive grains of the shaped grinding wheel for the same height.
In order to improve the processing effect of the large-abrasive-grain superhard abrasive grinding wheel, scholars at home and abroad carry out a lot of researches on laser shaping of the electroplated diamond grinding wheel and the superhard abrasive grinding wheel. For example, laser dressing has proven to be an effective method of dressing diamond grinding wheels to achieve efficient dressing of superabrasive grinding wheels. In order to obtain the surface profile precision information of the grinding wheel, the laser displacement sensor detects the circular runout of the electroplating and sintering grinding wheel, and the profile shape precision of the in-place grinding wheel can be obtained. In order to obtain the characteristics of the geometric shape, the surface appearance and the like of the abrasive particles on the surface of the grinding wheel, the surface of the grinding wheel is observed mainly by a Scanning Electron Microscope (SEM), an optical microscope, a White Light Interferometer (WLI) and the like. However, because the surface area of the grinding wheel is relatively large, the above detection means are mostly limited in a small detection range, and it is difficult to obtain the topographic data of the whole circumferential surface of the grinding wheel, and the comprehensive evaluation and analysis of the topographic data of the whole circumferential surface of the grinding wheel cannot be realized.
Disclosure of Invention
The problem that the height information of all abrasive particles of the whole large-abrasive-particle superhard abrasive grinding wheel is difficult to acquire and the high-performance evaluation is difficult is solved. The invention provides a method for evaluating the contour of abrasive particles of a large-abrasive-particle superhard abrasive grinding wheel, which is used for establishing a full-data acquisition-image processing abrasive-particle contour evaluation method based on a laser detection technology and an image processing technology, can realize the acquisition and comprehensive evaluation of the topographic information of the surface of the whole grinding wheel and provides technical guidance for the contour of the abrasive particles of the grinding wheel.
The invention is realized by the following steps:
the method for evaluating the equal altitude of the abrasive particles of the large-abrasive-particle super-hard abrasive grinding wheel is characterized by comprising the following steps of:
acquiring three-dimensional data information of the surface of a large-abrasive-particle superhard abrasive grinding wheel, and removing singular points;
step two, noise points are removed;
thirdly, analyzing the connected domains of the image without the noise points in the second step, finding out and marking each connected domain in the image, and preliminarily obtaining the quantity of the abrasive particles by adopting a seed filling method;
step four, corrosion treatment of the connected domain: further denoising before the abrasive particle quantity statistics by using corrosion operation, wherein the obtained connected domain quantity is the quantity of the abrasive particles;
step five, analyzing the high-performance evaluation results of the abrasive particles: obtaining each interval after binarization image processing such as singular point and noise point removal, connected domain analysis, image corrosion and the likehThe number of diamond abrasive grains of the height reference plane; the distribution rule of the abrasive grain exposure height before and after the shaping of the large-abrasive-grain superhard abrasive grinding wheel is obtained by analyzing the abrasive grain exposure height.
Further, the first step specifically comprises:
1.1, firstly, adjusting a mounting fixture, measuring by using a dial indicator to ensure that the circular runout of the grinding wheel is less than 10 microns, and then detecting and collecting three-dimensional data of the surface of the grinding wheel before and after shaping by using an ultra-high speed profile measuring instrument;
1.2, importing the point cloud data of the grinding wheel surface detected by the ultra-high speed profile measuring instrument into data point processing software for data processing, and carrying out height value
Carrying out distribution statistics; the three-dimensional point cloud data is represented as:
wherein m and n are the number of points in the measurement result along the x direction and the y direction respectively;
and 1.3, selecting the range of peak singular points and valley singular points according to the abrasive particle size number, determining a height reference plane, and repairing the singular points again by using a two-dimensional linear difference function after determining the singular points.
Further, the data point processing software comprises MATLAB or Python.
Further, the second step is specifically as follows:
2.1, importing the point cloud data with the singular points removed into data point processing software; since the detection environment, surface impurities and defects cause noise during data acquisition, they should be removed; traversing each point on the point cloud, determining a 5 multiplied by 5 kernel as a neighborhood by taking each point as a center, and calculating the absolute value of the height difference between each point and a center point in the neighborhood:
wherein,iis thatxThe number of the direction points is the same as the number of the direction points,jis thatyThe number of points in the direction of the direction,tis thatz(i, j) the number of points around;
2.2, arranging the calculated values according to the size, and taking the value positioned at the middle position in the sequencing set as the value of the central point after median filtering; the noise point removing principle is that the detected point is larger than a set height threshold, namely:
and 2.3, respectively selecting the binarized images processed by the datum plane data point processing software at different heights to remove singular points and noise points to obtain the binarized images of the abrasive particles.
Further, the large-abrasive-particle superhard abrasive grinding wheel comprises a brazed diamond grinding wheel with orderly-arranged abrasive particles, a CBN grinding wheel with orderly-arranged abrasive particles, an electroplated large-abrasive-particle diamond grinding wheel and a CBN grinding wheel.
Furthermore, the connected domain in the third step refers to an image region which is formed by foreground pixels with the same pixel value and adjacent positions in the image; the seed filling method is a seed-filing seed filling method, namely selecting a target pixel point as a seed, and combining target pixels adjacent to the seed into the same pixel set according to two basic conditions of a connected region, namely the pixel values are the same and the positions are adjacent to each other, and regarding the target pixels as abrasive grains.
Furthermore, the connected component erosion in the fourth step is to set the structural elements which can be in any shape as a set B along the vectorxAfter translation, the obtained set is completely contained in the binary image target area set A, and then the set of all vector end points meeting the condition forms the result of the corrosion of the image A by the structural element B and is recorded as the result
。
Further, in the fifth step, the reference surface is selected to be specific per a certain height interval according to the average particle size of the abrasive grainshValues, including 10 μm, 15 μm, 20 μm, or 25 μm.
Compared with the prior art, the invention has the beneficial effects that: 1) the invention can carry out data acquisition on the surface landform of the whole diamond grinding wheel; 2) the invention uses a method combining data processing and image processing to process data, and can realize high-efficiency evaluation of the high-grade of all abrasive particles on the surface of the large-abrasive-particle superhard abrasive grinding wheel.
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FIG. 1 is a flow chart of a method for evaluating the contour of the abrasive particles of the large-abrasive-particle superhard abrasive grinding wheel;
FIG. 2 is a diagram illustrating the acquisition of three-dimensional data of the surface of a large-abrasive-particle superhard abrasive grinding wheel ultra-high-speed profile measuring instrument according to the invention;
FIG. 3 is a binarized graph of the local abrasive grain original morphology, singular point removal and noise point removal of the large-abrasive-grain superabrasive grinding wheel according to the invention;
FIG. 4 illustrates a manner of acquiring abrasive grains by connected component analysis according to an embodiment of the present disclosure;
FIG. 5 is a comparison graph of a binarized image before and after etching according to an embodiment of the present invention;
FIG. 6 is a binarized image of diamond abrasive grains per reference surface with a pitch of 50 μm according to an embodiment of the present invention;
FIG. 7 shows the distribution of the exposed height of the abrasive grains before and after truing of the superabrasive wheel with large abrasive grains according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention more clear, the present invention is further described in detail by the following examples. It should be noted that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in FIG. 1, the method for evaluating the contour of the large-abrasive-grain superabrasive grinding wheel abrasive grains comprises the following steps:
before the large-abrasive-grain superhard abrasive grain grinding wheel is shaped, the three-dimensional data of the surface of the grinding wheel before and after laser shaping is detected by using an ultra-high-speed profile measuring instrument, as shown in figure 2. And a dial indicator is adopted to ensure that the circular runout of the grinding wheel is within 10 mu m. And obtaining the quantity of the diamond abrasive particles of the reference surface at a specific height (h) at intervals by removing singular points and noise points, analyzing a connected domain, corroding an image and the like. And finally, carrying out rule analysis and research on the abrasive particle exposure height information. The specific evaluation steps are as follows:
step 1: singular point removal
First, three-dimensional data of the surface of the grinding wheel before and after shaping is detected by using an ultra-high-speed profile measuring instrument (KEYENCE, LJ-V7060, Japan). Before detection, the circular runout of the grinding wheel is guaranteed within a certain range by adjusting the mounting fixture (a dial indicator is adopted for measurement).
And then, importing the point cloud data of the grinding wheel surface detected by the ultra-high speed profile measuring instrument into MATLAB, and carrying out height value distribution statistics.
And selecting the range of peak singular points and valley singular points according to the abrasive grain number, determining a height reference plane, and repairing the singular points again by using a two-dimensional linear difference function after determining the singular points.
Step 2: noise removal
And importing the point cloud data with the singular points removed into MATLAB. Since the detection environment, surface impurities, defects, and the like may cause noise during data acquisition, they should be removed. And traversing each point on the point cloud, determining a 5 multiplied by 5 kernel as a neighborhood by taking each point as a center, and calculating the absolute value of the height difference between each point and a central point in the neighborhood.
Then, the calculated values are arranged according to the size, and the value positioned at the middle position in the sorted set is taken as the value of the central point after median filtering. The noise point removing principle is that the detected point is larger than a set height threshold value. And respectively selecting the binarized images processed by MATLAB reference surfaces with different heights to remove singular points and noise points to obtain the binarized images of the abrasive particles.
And step 3: and identifying the quantity of the abrasive particles.
And analyzing the connected domains of the binary image, finding out and marking each connected domain in the image, and preliminarily obtaining the number of the abrasive particles by adopting a seed-filing seed filling method.
And 4, step 4: and (5) corrosion treatment of the connected region.
By using corrosion operation, undersize meaningless points can be eliminated, so that further denoising is performed before the abrasive particle quantity statistics is performed, and the quantity of the obtained connected domains is the quantity of the abrasive particles.
And 5: analysis of results of evaluation of contour of abrasive grains
And obtaining the quantity of the diamond abrasive particles of the reference surface at a specific height (h) at intervals by removing singular points and noise points, analyzing a connected domain, corroding an image and the like. The distribution rule of the abrasive grain exposure height before and after the shaping of the large-abrasive-grain superhard abrasive grinding wheel is obtained by analyzing the abrasive grain exposure height.
The method of the present invention is described below by way of specific data:
example 1:
and detecting the three-dimensional data of the surface of the brazed diamond grinding wheel with the orderly arranged abrasive grains before and after shaping by using an ultra-high-speed profile measuring instrument (KEYENCE, LJ-V7060, Japan). Before detection, the circular runout of the grinding wheel is ensured to be within 10 mu m by adjusting the mounting fixture (a dial indicator is adopted for measurement). Wherein, the measuring range of the ultra-high speed profile measuring instrumentzThe axis is 60 mm plus or minus 8 mm,xaxis 15 mm, repeat accuracy:zthe axis of the shaft is 0.4 μm,xaxis 5 μm, spot diameter: about 21 mm × 45 μm, number of profile data: 800 spots, blue semiconductor laser, wavelength 405 nm, output power 10 mW, spot diameter about 21 mm × 45 μm, profile data interval: (xAxis) 20 μm, sampling frequency 1000 Hz, grinding wheel speed 10 rad/s. The process for acquiring the three-dimensional data of the ultra-high speed profile measuring instrument surface of the large diamond abrasive grain and superabrasive grinding wheel with orderly arranged abrasive grains is shown in figure 2. The surface morphology of the reshaped grinding wheel was examined using a three-dimensional video microscope (KEYENCE, KH-7700, Japan). Wherein,
wherein,
is the diameter of the large-abrasive-grain superhard abrasive grinding wheel,
。
and a dial indicator is adopted to ensure that the circular runout of the grinding wheel is within 10 mu m. And then, the abrasive grain exposure height is evaluated by adopting the established abrasive grain contour evaluation method of full data acquisition-image processing.
The evaluation procedure was as follows:
(1) eliminating singular points to make data reliable
Since the side surfaces of some diamond abrasive grains are almost the same as the laser detection direction of the ultra-high-speed profile measuring instrument, the incident laser cannot be reflected and received by the controller, so that the minimum value of the valley singular point is obtained. The peak singular point is the maximum value obtained by simultaneously reflecting the detection laser by the side surfaces of two adjacent diamond abrasive grains. Both of which need to be eliminated.
And importing the point cloud data of the grinding wheel surface detected by the ultra-high speed profile measuring instrument into MATLAB to carry out height value distribution statistics. The three-dimensional point cloud data may be represented as:
and selecting the range of peak singular points and valley singular points according to the abrasive grain number, determining a height reference plane, and repairing the singular points again by using a two-dimensional linear difference function after determining the singular points.
(2) Noise removal to make data more reliable
And importing the point cloud data with the singular points removed into MATLAB. Since the detection environment, surface impurities, defects, and the like may cause noise during data acquisition, they should be removed. Traversing each point on the point cloud, determining a 5 multiplied by 5 kernel as a neighborhood by taking each point as a center, and calculating the absolute value of the height difference between each point and a center point in the neighborhood:
wherein,iis thatxThe number of the direction points is the same as the number of the direction points,jis thatyThe number of points in the direction of the direction,tis thatz(i, j) number of surrounding points.
Then, the calculated values are arranged according to the size, and the value positioned at the middle position in the sorted set is taken as the value of the central point after median filtering. The noise point removing principle is that the detected point is larger than a set height threshold, namely:
the binary images processed by MATLAB of reference surfaces with different heights are respectively selected to remove singular points and noise points to obtain binary images of abrasive particles, and as shown in FIG. 3, (a) is a binary image of the original appearance of local abrasive particles of the large-abrasive-particle superhard abrasive grinding wheel, (b) is a binary image of the singular points of the local abrasive particles of the large-abrasive-particle superhard abrasive grinding wheel, and (c) is a binary image of the local abrasive particles of the large-abrasive-particle superhard abrasive grinding wheel after the noise points are removed.
(3) And identifying the quantity of the abrasive particles. Firstly, connected domain analysis is carried out on a binary image, each connected domain in the image is found out and marked, and the quantity of abrasive grains is obtained preliminarily by adopting a seed-filing seed filling method. The connected domain refers to an image area formed by foreground pixel points (acquisition targets) which have the same pixel value and are adjacent in position in the image. The seed filling method is to select a target pixel point as a seed, and then merge the target pixels adjacent to the seed into the same pixel set and regard the target pixels as a grain according to two basic conditions (the pixel values are the same and the positions are adjacent) of a connected region, as shown in fig. 4.
2) And (5) corrosion treatment of the connected region. By using the erosion operation, it is possible to eliminate the too small meaningless points, so that further denoising is performed before the statistics of the number of the abrasive particles, and the number of the connected domains obtained thereby is the number of the abrasive particles, as shown in fig. 5, where the left (a) diagram is before erosion and the right (b) diagram is after erosion. Erosion is the vectorial addition of a structuring element (set B), which may be of any shapexAfter translation, the obtained set is completely contained in the binary image target area set A, and then the set of all vector end points meeting the condition forms the result of the corrosion of the image A by the structural element B and is recorded as the result
。
The method for evaluating the isomorphism of the large-abrasive-particle superhard abrasive grinding wheel mainly comprises the steps of firstly adopting a dial indicator to ensure that the circular runout of the grinding wheel is within 10 mu m, then adopting an ultrahigh-speed profile measuring instrument to obtain three-dimensional data of the surface of the grinding wheel, and obtaining the quantity of diamond abrasive particles of a height reference surface of each interval of 25 mu m after carrying out binarization image processing such as singular point and noise point removal, connected domain analysis, image corrosion and the like. Fig. 6 shows a binarized image of diamond abrasive grains per reference plane having a pitch of 50 μm, where (a) h =50 μm, (b) h =100 μm, (c) h =150 μm, and (d) h =200 μm.
By analyzing the exposure heights of the diamond abrasive particles before and after laser shaping, the exposure heights of the diamond abrasive particles before pulse laser shaping of the large-abrasive-particle superhard abrasive grinding wheel with the abrasive particles orderly arranged are mainly concentrated in the range of 200-300 mu m, the proportion is about 80.5%, and the exposure heights of the diamond abrasive particles on the surface of the whole grinding wheel are approximately in normal distribution (see figure 7). However, the overall exposure height of the diamond grains after laser shaping is reduced, mainly concentrated at 150-225 μm, and the percentage is about 88.3%. The method is used for shaping the large-abrasive-particle superhard abrasive grinding wheel with the orderly-arranged abrasive particles by adopting the pulse laser shaping method, so that the contour of the abrasive particles can be obviously improved, and the evaluation efficiency is higher by adopting the method.
Example 2
The difference from example 1 is: this example adopts
The electroplated large-abrasive-grain superabrasive grinding wheel is used as a research object, and the grinding wheel is shaped by a mechanical method such as Cr12 stainless steel, oilstone and the like. And setting the rotating speed, the feeding speed, the dressing depth and the dressing time of the grinding wheel according to the diameter of the grinding wheel and the grain size number of the abrasive particles. And then the method is adopted to evaluate the contour of the grinding wheel abrasive particles.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that modifications can be made by those skilled in the art without departing from the principle of the present invention, and these modifications should also be construed as the protection scope of the present invention.
Claims (8)
1. The method for evaluating the equal altitude of the abrasive particles of the large-abrasive-particle super-hard abrasive grinding wheel is characterized by comprising the following steps of:
acquiring three-dimensional data information of the surface of a large-abrasive-particle superhard abrasive grinding wheel, and removing singular points;
step two, noise points are removed;
thirdly, analyzing the connected domains of the image without the noise points in the second step, finding out and marking each connected domain in the image, and preliminarily obtaining the quantity of the abrasive particles by adopting a seed filling method;
step four, corrosion treatment of the connected domain: further denoising before the abrasive particle quantity statistics by using corrosion operation, wherein the obtained connected domain quantity is the quantity of the abrasive particles;
step five, analyzing the high-performance evaluation results of the abrasive particles: obtaining each interval by removing singular points and noise points, analyzing a connected domain and processing an image corrosion binarization imagehThe number of diamond abrasive grains of the height reference plane; the distribution rule of the abrasive grain exposure height before and after the shaping of the large-abrasive-grain superhard abrasive grinding wheel is obtained by analyzing the abrasive grain exposure height.
2. The method for evaluating the contour of the large-abrasive-grain super-abrasive grinding wheel abrasive grains according to claim 1, wherein the first step is specifically as follows:
firstly, adjusting a mounting fixture, measuring by using a dial indicator to ensure that the circular runout of the grinding wheel is less than 10 mu m, and then detecting and collecting three-dimensional data of the surface of the grinding wheel before and after shaping by using an ultra-high speed profile measuring instrument;
introducing the point cloud data of the grinding wheel surface detected by the ultra-high speed profile measuring instrument into data point processing software for data processing, and carrying out height value
Carrying out distribution statistics; the three-dimensional point cloud data is represented as:
wherein m and n are the number of points in the measurement result along the x direction and the y direction respectively;
and selecting the range of the peak singular point and the valley singular point according to the abrasive particle size number, determining a height reference plane, and repairing the singular point again by using a two-dimensional linear difference function after determining the singular point.
3. The method of claim 2, wherein the data point processing software comprises MATLAB or Python.
4. The method for evaluating the contour of the large-abrasive-grain super-abrasive grinding wheel abrasive grains according to claim 1, wherein the second step is specifically as follows:
importing the point cloud data from which the singular points are removed into data point processing software; since the detection environment, surface impurities and defects cause noise during data acquisition, they should be removed; traversing each point on the point cloud, determining a 5' 5 nucleus as a neighborhood by taking each point as a center, and calculating an absolute value of a height difference between each point in the neighborhood and the center point:
wherein,iis thatxThe number of the direction points is the same as the number of the direction points,jis thatyThe number of points in the direction of the direction,tis thatz(i, j) the number of points around;
arranging the calculated values according to the size, and taking the value positioned at the middle position in the sequencing set as the value of the central point after median filtering; the noise point removing principle is that the detected point is larger than a set height threshold, namely:
and respectively selecting the binarized images processed by the datum plane data point processing software at different heights to remove singular points and noise points to obtain the binarized images of the abrasive particles.
5. The method for evaluating the isomorphism of the abrasive particles of the large-abrasive-particle superhard abrasive grinding wheel according to claim 1, wherein the large-abrasive-particle superhard abrasive grinding wheel comprises a brazed diamond grinding wheel with orderly-arranged abrasive particles, a CBN grinding wheel with orderly-arranged abrasive particles, an electroplated large-abrasive-particle diamond grinding wheel and a CBN grinding wheel.
6. The method for evaluating the isotacticity of the large-abrasive-grain super-abrasive grinding wheel abrasive grains according to claim 1, wherein the connected domain in the third step refers to an image area which is formed by foreground pixel points with the same pixel value and adjacent positions in the image; the seed filling method is a seed-filing seed filling method, namely selecting a target pixel point as a seed, and combining target pixels adjacent to the seed into the same pixel set according to two basic conditions of a connected region, namely the pixel values are the same and the positions are adjacent to each other, and regarding the target pixels as abrasive grains.
7. The method for evaluating the contour of a large-abrasive-grain superabrasive grinding wheel abrasive grain according to claim 1, wherein the erosion of the connected component in the fourth step is carried out by using a structural element which may be an arbitrary shape as a set B and following a vectorxAfter translation, the obtained set is completely contained in the binary image target area set A, and then the set of all vector end points meeting the condition forms the result of the corrosion of the image A by the structural element B and is recorded as the result
。
8. The method for evaluating the contour of abrasive grains in a large-abrasive-grain super-hard abrasive grinding wheel according to claim 1, wherein in the fifth step, the specific height reference surface is selected according to the average grain size of the abrasive grainshValues, including 10 μm, 15 μm, 20 μm, or 25 μm.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114491836A (en) * | 2021-12-30 | 2022-05-13 | 华侨大学 | Virtual diamond tool generation method based on image processing and data driving |
| CN115035303A (en) * | 2022-06-17 | 2022-09-09 | 郑州磨料磨具磨削研究所有限公司 | Method for detecting abrasive concentration of electroplated colored cBN grinding wheel |
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| CN115239736B (en) * | 2022-09-23 | 2022-12-13 | 海安玻克超硬材料有限公司 | Method for monitoring quality of mixed material of abrasive layer for production of diamond-impregnated wheel |
| CN115684183A (en) * | 2022-12-01 | 2023-02-03 | 长春工业大学 | Grinding wheel dressing quality detection and evaluation method |
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